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At least 505 records · Page 28

Staying Competitive in Clean Manufacturing: Insights on Barriers from Industry Interviews

While industrial emissions research has historically focused on energy-intensive sectors like steel, cement, and chemicals, this study addresses a critical gap by examining barriers across all the manufacturing industry in the U.S. Sectors like food processing, retail, plastics, and transportation face unique challenges distinct from heavy industry, operating on thin margins with limited bargaining power while experiencing heightened consumer and stakeholder pressure for improved environmental responsibility. Through structured interview data collection process and using quantitative ratings and qualitative analysis, this research identifies and categorizes emission reduction barriers across four key themes: financial, technical, organizational, and regulatory. Unlike energy-intensive industries that may pursue hydrogen or carbon capture technologies, discrete manufacturing industry like automotive, electrical and electronics, and machine manufacturers typically focus on energy efficiency, electrification of thermal processes, and alternate fuel switching, solutions better aligned with their lower-temperature processes and distributed facility profiles. The study’s primary contribution lies in documenting specific barrier manifestations within organizations and identifying proven mitigation strategies that companies have successfully implemented or observed among peers.

business competitiveness↗

Thermal Barrier Coatings Overview: Design, Manufacturing, and Applications in High-Temperature Industries

Today’s competitive world economy is creating an indispensable demand for increased efficiency of engineering components that operate in harsh environments (i.e., very high-temperature, corrosive, or neutron irradiation environments), for applications in the energy, automotive, aerospace, electronics, and power industries. Increased research is being done on thermal barrier coatings (TBCs) for protecting such components, since the versatility of manufacturing techniques and the scale of deployment result in increased life, economics, performance, and durability. This review focuses on the advances that led to using TBCs for component life extension and, more recently, as an integral part of advanced component design for high-temperature and other types of harsh environments, such as those found in nuclear-related applications. Furthermore, factors that led to state-of-the-art advanced coating-fabrication techniques [e.g., electron-beam physical vapor deposition (EB-PVD), plasma spray deposition, and electrophoretically deposited TBCs, as well as functionally graded material (FGM) manufacturing] have also been emphasized in current coating R&D. This review explores the current state of TBCs, i.e., the latest advances regarding their fabrication and performance, associated challenges, and recommendations for their future use in aerospace, nuclear, high-temperature, or otherwise harsh environments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Messaging for Impact: Behavioral Science-Based Communication Strategies to Advance Energy Efficiency

Currently, five legal authorities require U.S. federal agencies to purchase energy-efficient products. However, compliance with these requirements has consistently been low (~55%). Recent surveys indicate that energy efficiency requirements are not communicated properly within federal agencies and energy-efficiency is not a top priority. In the constantly evolving energy industry, with many solutions for a clean energy future, effective communication methods are vital for widespread adoption of energy efficiency. We have been conducting experiments within the U.S. federal sector that test the effectiveness of messaging strategies developed by using behavioral science principles like loss aversion, framing, and herd behavior. This will identify effective communications methods that encourage energy efficiency adoption. In this study, we measure the effectiveness of different communication strategies by monitoring the web traffic of hyperlinks placed within our digital communications and outreach materials. To determine effective strategies that influence federal buyer behavior, the web traffic from subjects that received the behavioral science-based messaging (treatment group) is compared to that from subjects that received regular messaging (control group) for each of the strategies. This paper provides an overview of the behavioral science principles that we applied, data collection methods, and results of our analysis. Since the lack of effective communication of energy-efficiency policies is also a common problem in the private sector, the messaging strategies developed in this study can be applicable to other large private sector institutions

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Application of Core Theory to the Airline Industry

Competition in the airline industry has been fierce since the industry was deregulated in 1978. The proponents of deregulation believed that more competition would improve efficiency and reduce prices and bring overall benefits to the consumer. In this paper, a case is made based on core theory that under certain demand and cost conditions more competition can actually lead to harmful consequences for industries like the airline industry or cause an empty core problem. Practices like monopolies, cartels, price discrimination, which is considered inefficient allocation of resources in many other industries, can actually be beneficial in the case of the airline industry in bringing about an efficient equilibrium.

Raghavan, Sunder↗

Recent Advances in 3D Printed Sensors: Materials, Design, and Manufacturing

Sensors are of great importance in different aspects of research and industry. Future sensors will require high-efficient and low-cost manufacturing, as well as high-performance functionality in areas, such as mechanical sensing, biomedical, and optical applications. Recent advances in 3D printing open a new paradigm for sensors fabrication as a precision, customizable, and seamless process. Here, in this article, the state-of-the-art 3D printing methods in sensors manufacturing is reviewed and the performance of the 3D printed sensing materials and devices is summarized. Special attention is paid to emerging multimaterial printing and 4D printing technologies, which will benefit the fabrication of a new generation of structures with multifunctionalities. The content on 3D printed sensors covers piezoelectric sensors, medical, and optical sensing devices. The performance of 3D printed sensors in comparison with the sensors made by traditional manufacturing is also covered. Finally, section 4 provides the viewpoints on the future development of 3D printed sensors.

36 MATERIALS SCIENCE↗

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗

Technical and economic evaluation of heat transfer fluids for a TES system integrated to an advanced nuclear reactor

The utilization of thermal energy storage technology has emerged as a potential enhancement for nuclear power plants. Although nuclear energy systems possess the ability to adjust their energy output, prolonged variations in production can impact the plant's overall efficiency and economic viability. However, the nuclear industry can capitalize on thermal energy storage to bolster the power plant's economics by leveraging ancillary services and market hedging strategies. Here this research aims to advance the development of thermal energy storage for advanced nuclear reactors by assessing the thermophysical properties of various heat transfer fluids, including FLiNaK, KCl-MgCl 2 , LiCl-KCl, (LiNaK) 2 CO 3 , NaF-ZrF 4 , and KF-ZrF 4 , at temperatures ranging from 500 to 900oC. The assessment is conducted based on thermophysical correlations established in previous studies and employs figures of merit as a metric to evaluate the heat transfer performance of different salt candidates. Additionally, a cost analysis is conducted to provide an idea of the potential cost associated with each salt candidate.

25 ENERGY STORAGE↗

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials↗

Real-time cure monitoring of fiber-reinforced polymer composites using infrared thermography and recursive Bayesian filtering

Despite the desirable characteristics of fiber-reinforced polymer (FRP) composites, their utilization in high volume production industries is limited by a lack of efficient manufacturing techniques. Monitoring the curing process of these composites can help with improving the quality and efficiency of the manufacturing process. This article discusses a method that uses Kalman-filter-based fusion of the information obtained from infrared thermography (surface temperature measurements) and a heat conduction model to estimate degrees of cure and internal temperatures of curing FRP composite parts in real time. The effectiveness of the methodology is demonstrated by successfully monitoring the curing of an FRP composite part in a laboratory experiment. Finally, the proposed methodology is a crucial step towards identifying anomalies in the curing process that negatively impact the quality of FRP composite parts.

36 MATERIALS SCIENCE↗

Shear assisted processing and extrusion of enhanced strength aluminum alloy tubing

Hollow extrusions are used in many industries to make strong, lightweight, and affordable structures. Shear Assisted Processing and Extrusion (ShAPE) enables the extrusion of many alloys, often with noteworthy properties. In this investigation, ShAPE was used to extrude 1 and 2 mm wall tubes of aluminum alloy 6063 measuring 12 mm in diameter at extrusion speeds up to 3.8 m/min. This speed is 10 and 15 times faster than has been reported for any alloy using ShAPE and friction stir back extrusion, respectively. Increasing the extrusion speed from 0.7 to 3.8 m/s resulted in using 68% less process energy at steady state. Microstructural analysis and tensile testing were performed on as-extruded tubes and tubes with a direct T5 heat treatment. Grain refinement from 65 µm to below 20 µm was observed. Growth of macroscale Mg 2 Si strengthening precipitates was not observed. ShAPE processing resulted in recrystallization, and extrusion speed was shown to influence final extrudate texture. Here, transmission electron microscopy analysis revealed that the as-extruded microstructure was free of nanoscale ß" strengthening precipitates. Nanoscale ß" was prominent in direct-aged (T5) ShAPE tubes, similar to a slightly over-aged conventional T6 microstructure. As-extruded tubes had ultimate tensile strengths on par with conventional T5 extrusions and approximately double the total elongation. Tubes that underwent a T5 heat treatment had yield and ultimate strengths averaging 198 and 234 MPa, respectively, with an average total elongation of 11%. The tensile test results are comparable to a conventional T6 heat treatment, but without the solutionization heat treatment step. Mechanical properties either remained flat or improved with increased extrusion speed, which suggests that ShAPE can be scaled up to an industrial process to create energy- and economically efficient high-strength extrusions.

36 MATERIALS SCIENCE↗

On the high-temperature stability of the Al 8 Cu 3 Ce intermetallic in an additively manufactured Al-Cu-Ce-Zr alloy

High-temperature resistant eutectic Al alloys are crucial materials for lightweight and energy efficient design in the automotive and aviation industries. Additive manufacturing offers a pathway to refine eutectic microstructures and develop novel alloys with superior high-temperature strength. High-volume fraction intermetallic Al-Cu-Ce alloys have been developed to deliver high-temperature strength in combination with reduced hot-tearing susceptibility. Zr is added to provide additional strengthening via nanoscale Al 3 Zr precipitation, and to stabilize and avoid coarsening of the Al 8 Cu 3 Ce phase. However, the detailed interaction between Zr and Al 8 Cu 3 Ce remains unexplored. In this work, we show with synchrotron X-ray diffraction that laser powder bed fusion fabricated Al-Cu-Ce and Al-Cu-Ce-Zr alloys contain predominantly the Al 8 Cu 3 Ce intermetallic in the as-fabricated condition. Heat treatment of the Al-Cu-Ce alloy results in the Al 8 Cu 3 Ce → Al 8 Cu 4 Ce phase transformation. In the Al-Cu-Ce-Zr alloy, minor fractions of (Al,Cu,Si) 4 Ce and Al 2 Cu-θ are found in the as-fabricated condition, while Al 8 Cu 3 Ce remains stable during heat treatment. Atom probe microscopy quantifies intermetallic stoichiometries and reveals how Zr is enriched at the Al-matrix/Al 8 Cu 3 Ce interface acting as a diffusion barrier against solute exchange. Calibrated thermodynamic modeling underpins this as a kinetic effect. Here, a qualitative microstructural model summarizes, how Zr stabilizes Al 8 Cu 3 Ce against phase transformations and coarsening.

36 MATERIALS SCIENCE↗

Surface engineering of polymeric membranes with metal oxides for improved fouling resistance and superior oil-water separation

Rapid industrial growth has increased the need for efficient membranes to separate oil-water emulsions. Polyvinylidene fluoride (PVDF) membranes, although widely used due to their chemical inertness and favorable mechanical properties, suffer from fouling due to their intrinsic hydrophobicity. Modifying these membranes after fabrication offers a practical solution as it easily fits into existing large-scale manufacturing processes. Atomic layer deposition (ALD), an atomically-precise vapor phase surface modification technique, can create ultrathin metal oxide layers that greatly improve membrane hydrophilicity without significantly affecting the original pore size. However, PVDF's lack of reactive chemical moieties makes ALD challenging. Here, in this study, we present a simple alkali treatment that greatly enhances ALD nucleation and growth on PVDF membranes. This treatment imparts exceptional oil-water emulsion separation capabilities and antifouling behavior in PVDF membranes after just a few ALD cycles, surpassing the performance of PVDF membranes coated with hundreds of ALD cycles. This dramatic reduction in the number of ALD cycles required could enable cost-effective modification of commercial PVDF membranes at scale using spatial, roll-to-roll ALD. These modified membranes outperform reported modified PVDF membranes, with >99 % permeance recovery and <1 % irreversible loss of permeance and >98 % oil rejection from oil-water emulsions over 100 h continuous operation, making them promising for advanced water purification technologies.

Atomic layer deposition↗

Friction stir processing on a strontium modified, thin-wall, vacuum-assisted high-pressure die-cast Aural-5 alloy to improve tensile and fatigue performance

Here, this study explores the application of friction stir processing (FSP) to enhance the material properties of Sr-modified Aural-5 alloy, with a focus on improved tensile and fatigue properties. Aural-5 is a well-known vacuum-assisted high-pressure die-cast (HPDC) Al-Si7-Mg alloy used in the automotive industry to reduce vehicle weight, enhance fuel efficiency, and lower carbon emissions. This alloy modifies its material chemistry with Sr for fine fibrous networks of eutectic silicon and manganese (Mn) to reduce die soldering. It has significantly less iron (Fe) content resulting in the elimination of detrimental needle-shaped Fe-bearing ß-phase intermetallic and improving ductility. The initial microstructure of as-received HPDC Aural-5 exhibits shrinkage porosity in the middle section, a dendritic microstructure with fibrous Al-Si eutectic colonies, a shear-band structure beneath the die-wall, large dendritic externally solidified crystals (ESCs), needle-shaped Mg 2 Si phase and significant second-phase particulates. Some of those microstructural features, such as porosity, ESCs, needle-shaped Mg 2 Si phase, and large second-phase particles, serve as initiation sites for cracks under mechanical loading, resulting in adverse effects on tensile properties, particularly ductility. FSP effectively transforms the microstructure into a wrought configuration with uniform particle distribution by eliminating porosity and disintegrating dendrites, eutectic colonies, ESCs, second-phase particles, and shear-band structures. FSP-driven microstructure modification enhances yield strength and tensile ductility by ~30% and ~35%, respectively. The fatigue life of the material in a bending mode configuration (stress ratio R = 0.1) after FSP exhibits enhancements ranging from 2.0 to 3.9 times that of the original HPDC Aural-5 alloy, depending on the applied stress level.

36 MATERIALS SCIENCE↗

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Feasibility study of Mg storage in a bilayer silicene anode via application of an external electric field

With the goal of developing a Si-based anode for Mg-ion batteries (MIBs) that is both efficient and compatible with the current semiconductor industry, the current research utilized classical Molecular Dynamics (MD) simulation in investigating the intercalation of a Mg 2+ ion under an external electric field (E-field) in a 2D bilayer silicene anode (BSA). First principles density functional theory calculations were used to validate the implemented EDIP potentials. Our simulation shows that there exists an optimum E-field value in the range of 0.2–0.4 V Å –1 for Mg 2+ intercalation in BSA. To study the effect of the E-field on Mg 2+ ions, an exhaustive spread of investigations was carried out under different boundary conditions, including calculations of mean square displacement (MSD), interaction energy, radial distribution function (RDF), and trajectory of ions. Our results show that the Mg 2+ ions form a stable bond with Si in BSA. The effects of E-field direction and operating temperature were also investigated. In the X–Y plane in the 0°–45° range, 15° from the X-direction was found to be the optimum direction for intercalation. The results of this work also suggest that BSA does not undergo drastic structural changes during the charging cycles with the highest operating temperature being ~300 K

25 ENERGY STORAGE↗

On the design and performance of InGaN/Si double-junction photocathodes

Via a combined theoretical and experimental study, we have investigated the synthesis and performance characteristics of InGaN/Si double-junction photoelectrochemical (PEC) water splitting devices, which promise a theoretical solar-to-hydrogen conversion efficiency ~30% under AM 1.5G one-sun illumination. The double-junction photocathodes consist of a p + -InGaN top light absorber and a Si bottom p-n junction, which are connected through a nanowire tunnel junction. The effect of indium composition of the top light absorber as well as the impact of p-type Mg dopant incorporation on the PEC performance was studied. Experimentally, the sample with 32% indium composition showed a maximum photocurrent density of ~9 mA/cm 2 at 0.4 mV vs reverse hydrogen electrode (RHE) with applied bias photon-to-current efficiency (ABPE) of ~9.5%. An optimum p-type doping level ~1 × 10 17 cm -3 was also identified, which results in the best device performance as a result of optimum surface band bending as well as vertical charge carrier (hole) transport. These results also show a good agreement with our theoretical analysis. This work provides significant insights in advancing the design and development of high efficiency PEC devices for artificial photosynthesis using industry ready materials, e.g., Si and GaN, to achieve large-scale, low-cost onsite hydrogen fuel production.

42 ENGINEERING↗

An improved method for quantitatively measuring antifouling coating performance using a mussel single thread tensile adhesion test

Surface biofouling reduces the efficiency and lifespan of equipment across many industries. The development of high-performance antifouling surfaces, such as foul release coatings, benefits from test methods that can quickly identify superior antifouling surfaces in the laboratory during material development. Existing test methods poorly discriminate between different foul release coatings. Here is presented a method to assess the ability of surfaces to resist mussel adhesion using a quantitative, controlled single thread adhesion test (STAT) method, allowing for meaningful comparisons between low adhesion foul release surfaces. This method provides greater accuracy and finer resolution than push-based mussel shear adhesion methods without the difficulties associated with mussel size, thread attachment angle, or harming the mussels. The single thread tensile method is demonstrated on a variety of standard and high-performance coatings, and it is shown that the method detects differentiation between commercial foul release coatings that could not be resolved using other methods.

42 ENGINEERING↗

Future of Energy Efficiency in Buildings: Drivers and Market Expectations [Slides]

This slide-deck report identifies drivers of energy efficiency in buildings over the next 10 years, for all fuels. The report also provides insights on what the future of efficiency may look like in that time period and considers other distributed energy resources, as well as decarbonization and demand flexibility, to the extent they are intertwined with efficiency activities. Understanding market drivers and possible future market attributes for energy efficiency can help policy makers, regulators and industry make informed decisions—for example, how best to design policies and investments to support desired outcomes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗